Novel photon-counting low-dose computed tomography using a multi-pixel photon counter

Morita, Hayato; Oshima, T.; Kataoka, J.; Arimoto, M.; Nitta, H.

doi:10.1016/j.nima.2017.02.015

Cited by 19 publications

(5 citation statements)

References 15 publications

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“…The recovery time, or the photon-counting rate of SiPM is determined by the finite time taken to quench the avalanche, then reset the diode voltage to its initial bias value. This is essential for high flux photon detection in such applications as photon counting computer tomography (CT) [4][5][6], which involves a high photon-counting rate and has potential to reduce the exposure time and radiation dose. If the photon-counting rate of SiPM could be increased to hundreds of MHz or GHz, it could be applied in photon reflectometry, quantum random number generators [7][8][9], etc.…”

Section: Introductionmentioning

confidence: 99%

Recovery Time of Silicon Photomultiplier with Epitaxial Quenching Resistors

et al. 2017

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Abstract:The silicon photomultiplier (SiPM) is a promising semiconductor device for low-level light detection. The recovery time, or the photon-counting rate of the SiPM is essential for high-flux photon detection in such applications as photon counting computer tomography (CT). A SiPM with epitaxial quenching resistors (EQR SiPM) has advantages in fabricating small APD microcells connected in series with lower quenching resistors, therefore, APD cells with a low RC time constant and a short recovery time can be expected. In this report, the recovery time of EQR SiPM has been investigated using both the double light pulse method and the waveform analysis method. The results show that the recovery time of EQR SiPM is strongly dependent on the size of the active area and the number of fired pixels. For a 3 × 3 mm 2 device, while total about 90,000 pixels were fired, the recovery time was 31.1 ± 1.8 ns; while fired pixels were controlled to about 2000, the recovery time decreased significantly to 6.5 ± 0.4 ns; and the recovery time of one fired pixel was 3.1 ± 0.2 ns. For 1.4 × 1.4 mm 2 device, the recovery time was 15.2 ± 0.5 ns, while a total of about 20,000 pixels were fired. Effects that may affect the recovery time of the SiPM, including strength of the pulse light, signal transmission time delay, and the readout electronics are discussed.

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Section: Introductionmentioning

confidence: 99%

Recovery Time of Silicon Photomultiplier with Epitaxial Quenching Resistors

et al. 2017

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“…Advances in multi-detector technology, photon counting energy dispersive detectors and computer-processing technology have made spectral CT imaging possible [86][87][88][89][90][91][92][93][94]. Spectral CT can convert the X-ray absorption coefficient of any material to absorption coefficient of any two base material and achieve the same attenuation effect.…”

Section: Spectral Ctmentioning

confidence: 99%

Research Status and Prospect for CT Imaging

Liu¹

2018

State of the Art in Nano-Bioimaging

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Computed tomography (CT) is a very valuable imaging method and plays an important role in clinical diagnosis. As people pay more and more attention to radiation doses these years, decreasing CT radiation dose without affecting image quality is a hot direction for research of medical imaging in recent years. This chapter introduces the research status of low-dose technology from following aspects: low-dose scan implementation, reconstruction methods and image processing methods. Furthermore, other technologies related to the development tendency of CT, such as automatic tube current modulation technology, rapid peak kilovoltage (kVp) switching technology, dual-source CT technology and Nano-CT, are also summarized. Finally, the future research prospect are discussed and analyzed.

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“…Moreover, the MPPC-based PC-CT may more easily divert the knowledge of EiCT. Our previous studies demonstrated that the PC-CT system can potentially reduce the radiation dose as low as 1/100 level of EiCT, while retaining high image quality [6]. In reality, we successfully performed the simultaneous imaging of multiple contrast agents and estimated the absolute concentration [8,9].…”

Section: Introductionmentioning

confidence: 98%

“…To overcome such problems encountered in CdZnTe-based PC-CT, we propose a novel PC-CT system comprising a multipixel photon counter (MPPC) coupled with high-speed scintillators (∼ 70 ns) [6,7]. MPPCs feature a rapid temporal response (∼ 10 ns) and a high internal gain (∼ 10 6 ).…”

Section: Introductionmentioning

confidence: 99%

Application of machine-learning models to improve the image quality of photon-counting CT images

et al. 2021

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X-ray computed tomography (CT) has been widely used in medical diagnostic imaging. However, conventional, energy-integrated CT requires a high radiation dose and can only provide monochromatic images that cannot eliminate various artifacts. In contrast, photon-counting CT (PC-CT) provides low-dose multicolor CT imaging, which enables the identification of multiple contrast agents. However, in the PC-CT system, the lack of photon statistics, which is also caused by image reconstruction in the limited energy band, severely affects the image quality. In this study, we applied three types of machine-learning (ML) techniques to improved the image quality of PC-CT, that is, dictionary learning, U-Net, and Noise2Noise. These ML models were trained using low- and high-dose image pairs created in simple steps. The trained ML models were applied to simulated data, and experimental PC-CT images of contrast agents used in clinical practice. Consequently, in the simulated data, the peak signal-to-noise ratio (PSNR) value improved from 21.3 for the input to 26.6, 33.3, and 30.1 for dictionary learning, U-Net, and Noise2Noise, respectively. Furthermore, in the actual PC-CT images, we successfully reproduced PC-CT images with high PSNR, which enabled simultaneous imaging of multiple contrast agents with improved accuracy of concentration estimation. As a future perspective, we will develop a processing technique that can be applied to in vivo CT images.

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Novel photon-counting low-dose computed tomography using a multi-pixel photon counter

Cited by 19 publications

References 15 publications

Recovery Time of Silicon Photomultiplier with Epitaxial Quenching Resistors

Recovery Time of Silicon Photomultiplier with Epitaxial Quenching Resistors

Research Status and Prospect for CT Imaging

Application of machine-learning models to improve the image quality of photon-counting CT images

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